A.I. in medical imaging… a must-have, whatever it is.

December 11, 2018

One might think new technology that holds the promise to reduce medical costs, improve diagnoses, and raise patient comfort would make for exciting conversations in the medical imaging industry. Instead, the mere mention of A.I. today causes frequent and dismissive eye-rolls. A.I. is a term that has been co-opted by cooperate marketing machines that is now so vague as to be virtually meaningless. A.I., without specifics, ultimately does the medical imaging industry a disservice by obfuscating the continued technological evolution of its products and software. Sorry marketing folks, but I doubt there are many RFPs that insist on “the latest A.I. thing” be included. Features matter and nebulous visions do not. Luckily there are signs that we may have passed “peak A.I” and are getting back to more descriptive ways to showcase new imaging technologies.

The pendulum swings

Vendors seem to be picking up on this festering A.I. fatigue. For example, Phillips Healthcare went out of its way to put their own spin by promoting its “Adaptive Intelligence” instead of the more generic artificial intelligence. Siemens Healthineers was noticeably restrained in dishing out the AI speak, instead preferring to showcase capabilities available like automatic patient positioning for its CT scanners. “Compressed sensing” is not unique to any vendor, but nonetheless a perfect example of a specific feature, built on the processing of data and application of algorithms, to deliver real benefits. Mercifully, it was not shrouded in the veil of A.I. The focus on precision placement for reduced scan times and dosages was shared by most vendors. Perhaps the pendulum is finally swinging in the direction of specifics from the ambiguous.

Improving operational efficiency with analytics

Operational analytics is a promising application of data analytics. The combination of imaging device telemetry and technologist information can be harnessed for insights on radiology department performance metrics. GE Healthcare’s Edison platform is summarized with a slick dashboard interface for every statistic imaginable; total exams, average patient per hour, dose warning, and reject rate, among others. One can imagine what Henry Ford would do with such information at his fingertips.

Monetization of these products comes in different forms. Obviously, a subscription to such services can be a new and renewable revenue stream. Indeed, central to some software is its own estimate of cost savings. Little imagination is needed to see how the sales pitch for this tech goes; vendors will attempt to show that purchasing this software will pay for itself in short order. However, others see analytics offerings as a value-add to their existing after-sales service and support agreements.

Diagnostic assistance: walking the line

A Phillips Healthcare press event included some thoughts of Richard Wiggins, MD, Professor of Radiology and Imaging Sciences at the University of Utah Health. He described the current situation as “a scary time to be in radiology” and mentioned the fear among his cohorts that they may not have a job if five years with the continued march towards automatic analysis of medical images. Wiggins firmly disagreed and shared how his typical voluminous workload can be better managed with products like Philips’ Illmeo to help to bring order out of the chaos. Intelligence brought to the image review workflow should be welcomed, not feared, in his mind.

Other flavors of A.I.

United Imaging’s bold entry into the United States market (covered here by IHS Markit analyst Adam Davidson) included separate company to focus on A.I. in “United Imaging Intelligence,” though exactly what this organization would do was not revealed.

GE Healthcare is bringing computational muscle on-device for new products in its general radiography line. Fueled by Intel processors and Nvidia GPUs, GE showed off its “Critical Care Suite” with its first offering to assist in Pneumothorax detection. The idea is that a bad scan can be identified in real-time. Though facilities will have to wait as it has yet to clear FDA 510k certification.

The above are just a few examples of the genuine innovation happening in medical imaging dealing with the analysis of ever-increasing amounts of data. These hold the promise to deliver services more efficiently with increased patient comfort and safety. However, the industry would be well served to continue to distance itself from A.I. as an over-arching term and instead focus on the features that will make a difference.